OneLake Security & DLP: Fabric Governance Checklist
Workspace roles, OneLake security, and Purview DLP are three separate layers and configuring one doesn’t cover the others. The DefaultReader trap most teams miss.
Copilot in Microsoft Fabric: What It Actually Does
Copilot in Fabric is several separate tools, not one. Where it’s genuinely strong (DAX, PySpark), where it still needs a human, and what it costs from F2 upward.
The Relationship Between API, CLI, and MCP
One API, two doors. CLI and MCP aren’t rivals – they’re two clients of the same business logic, built for two different kinds of caller: humans and models.
MCP vs CLI vs API for AI Agents
CLI wins on token efficiency and reliability; MCP wins on discovery, typed I/O, and multi-tenant auth. A two-layer decision framework for choosing per integration, not per system.
Why MCP Needs a CLI: The Role of CLIs in Agent Tooling
MCP standardises how agents discover tools – it didn’t replace the execution layer. The strongest 2026 integrations build the CLI first and wrap it in MCP second.
Power BI Desktop Bridge
AI agents can edit Power BI reports. What they couldn’t do – until now is check whether the edit actually worked. The Power BI Desktop Bridge adds a validate-reload-screenshot loop that makes an AI agent look at its own output before calling the job done. Here’s where it earns its keep, and where it still needs a human in the room.
Power BI Copilot Default Activation: Enable or Disable?
Learn how to enable Power BI Copilot by default across your organisation and what admin settings control the rollout. Everything your Power BI admin needs to know before activation.
MLflow Microsoft Fabric: Data Science Lifecycle Guide
Microsoft Fabric has MLflow built in giving data scientists a native experiment tracking, model registry, and deployment workflow without any external tooling. Learn how to log experiments, compare runs, and register your best models directly from Fabric Notebooks.
Unlocking Hidden Potential of Your Data with AI
Most organisations are sitting on vast amounts of untapped data that AI can transform into actionable intelligence. Learn the practical first steps to unlocking your data potential with AI from data readiness to use case prioritisation.
Future of Data Analytics Is AI: How to Get Started
AI is fundamentally reshaping what data analytics means for enterprise teams from automated insights to natural language querying and predictive decision-making. This guide explores the trends, tools, and skills that will define the next five years of data analytics.
Data Analytics to AI in Power BI: The Transition Guide
Power BI is no longer just a reporting tool, it’s becoming the front end for AI-powered analytics with Copilot, Azure ML integration, and smart narratives. Learn how to bridge the gap between traditional BI and AI-driven decision intelligence using tools you already own.
AI Enhancing Data Analytics: Real-World Use Cases
AI isn’t a future concept, it’s already enhancing data analytics across finance, retail, healthcare, and operations today. This guide covers six real business scenarios where AI is delivering measurable improvements in speed, accuracy, and decision quality.